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首页> 外文期刊>BMC Medical Informatics and Decision Making >Measuring the effect of commuting on the performance of the Bayesian Aerosol Release Detector
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Measuring the effect of commuting on the performance of the Bayesian Aerosol Release Detector

机译：测量通勤对贝叶斯气溶胶释放探测器性能的影响

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BackgroundEarly detection of outdoor aerosol releases of anthrax is an important problem. The Bayesian Aerosol Release Detector (BARD) is a system for detecting releases of aerosolized anthrax and characterizing them in terms of location, time and quantity. Modelling a population's exposure to aerosolized anthrax poses a number of challenges. A major difficulty is to accurately estimate the exposure level--the number of inhaled anthrax spores--of each individual in the exposed region. Partly, this difficulty stems from the lack of fine-grained data about the population under surveillance. To cope with this challenge, nearly all anthrax biosurveillance systems, including BARD, ignore the mobility of the population and assume that exposure to anthrax would occur at one's home administrative unit--an assumption that limits the fidelity of the model.MethodsWe employed commuting data provided by the U.S. Census Bureau to parameterize a commuting model. Then, we developed methods for integrating commuting into BARD's simulation and detection algorithms and conducted two studies to measure the effect. The first study (simulation study) was designed to assess how BARD's detection and characterization performance are impacted by incorporation of commuting in BARD's outbreak-simulation algorithm. The second study (detection study) was designed to measure the effect of incorporating commuting in BARD's outbreak-detection algorithm.ResultsWe found that failing to account for commuting in detection (when commuting is present in simulation) leads to a deterioration in BARD's detection and characterization performance that is both statistically and practically significant. We found that a simplified approach to accounting for commuting in detection--simplified to maintain tractability of inference--nearly fully restored both detection and characterization performance of BARD detector.ConclusionWe conclude that it is important to account for commuting (and mobility in general) in BARD's simulation algorithm. Further, the proposed method for incorporating commuting in BARD's detection algorithm can successfully perform the necessary correction in the detection algorithm, while preserving BARD's practicality. In our future work, we intend to further study the problem of the trade-off between running time and accuracy of the computation in BARD's version that includes commuting and ultimately find the best such trade-off.
机译：背景技术尽早检测室外炭疽的气溶胶释放是一个重要的问题。贝叶斯气溶胶释放检测器（BARD）是一种用于检测气雾化炭疽的释放并根据位置，时间和数量对其特征进行表征的系统。对人群暴露于气溶胶​​性炭疽的暴露进行建模提出了许多挑战。一个主要的困难是要准确估计暴露区域中每个人的暴露水平，即吸入的炭疽孢子的数量。造成这种困难的部分原因是缺乏有关受监视人口的细粒度数据。为了应对这一挑战，包括BARD在内的几乎所有炭疽生物监视系统都忽略了人口的流动性，并假设接触炭疽病将在本人的家庭管理部门发生-这是一个限制模型保真度的假设。由美国人口普查局提供以参数化通勤模型。然后，我们开发了将通勤功能集成到BARD的仿真和检测算法中的方法，并进行了两项研究来测量效果。第一项研究（模拟研究）旨在评估将通勤纳入BARD的爆发模拟算法对BARD的检测和表征性能的影响。第二项研究（检测研究）旨在衡量将通勤纳入BARD爆发检测算法的效果。结果我们发现，在计算中未考虑通勤的情况（在模拟中存在通勤时）会导致BARD的检测和表征恶化具有统计意义和实践意义的性能。我们发现，一种简化的解决通勤问题的方法-简化以保持推理的可操作性-几乎完全恢复了BARD检测器的检测和表征性能。在BARD的仿真算法中。此外，所提出的将通勤并入BARD的检测算法中的方法可以成功地在检测算法中执行必要的校正，同时保持BARD的实用性。在未来的工作中，我们打算进一步研究运行时间与BARD版本的计算精度（包括通勤）之间的权衡问题，并最终找到最佳的权衡方法。

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